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This study evaluates the dynamic performance of a reference footbridge under human–structure interaction (HSI) effects using real-time hybrid simulation (RTHS). The footbridge, designed with precise multi-axial dynamic sensitivity, is tested under pedestrian gait velocities of 1.20, 1.50, and 1.80 m · s − 1 . The RTHS framework involves an analytical continuous model of the footbridge as a numerical substructure and real human gait loads as the experimental substructure. The results reveal significant dynamic coupling between pedestrian-induced loads and the responses of the structure. Lateral vibrations exhibit a fundamental frequency of approximately 1.0 Hz, whereas vertical vibrations peaked near 2.0 Hz. Dynamic synchronization, particularly at higher gait velocities, amplified the structural vibrations, with lateral loading increasing by up to 300% in the middle span. Vertical loads show substantial amplification and attenuation depending on gait velocity and footbridge location. Lateral accelerations display a dispersion of approximately 15.0%, whereas vertical accelerations showed higher variability, with dispersions reaching up to 20%. The RTHS technique demonstrates high fidelity and accuracy, with global errors below 2.95% and delays of less than 2.10 ms across all evaluated directions. These results emphasize the critical importance of accounting for HSI effects in the design of pedestrian footbridges because human-induced vibrations can significantly impact structural serviceability and user comfort. This study offers important insights into optimizing footbridge design to mitigate the risks of excessive vibrations and ensure both safety and functionality under typical pedestrian loads. [ABSTRACT FROM AUTHOR]

Pedestrian bridges, which are essential in urban and rural infrastructures, are vulnerable to vibrations induced by pedestrian traffic owing to their low mass, stiffness, and damping. This paper presents a novel predictive model of Human-Structure Interaction (HSI) that integrates a three-dimensional biomechanical model of the human body, and a pedestrian bridge represented as a simply supported Euler-Bernoulli beam. Using inverse dynamics, the human model accurately captures three-dimensional gait and its interaction with structural vibrations. The results show that this approach provides precise estimates of human gait kinematics and kinetics, as well as the bridge response under pedestrian loads. The incorporation of a three-dimensional human gait model reflects the changes induced by bridge vibrations, providing a robust tool for evaluating and improving the effect of structural vibrations on the properties and gait patterns. [ABSTRACT FROM AUTHOR]

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Pavement condition assessment is essential for roadway maintenance and rehabilitation processes. Image-based inspection methods provide information regarding the surface of the pavement and allow quantitative analyses of pavement conditions. A methodology for the detection of damages in the pavement, by applying pattern recognition and image analysis and machine learning algorithms, is presented in the paper. This methodology consists of image acquisition, image processing using the wavelet scattering transform (WST), feature extraction employing the fractal dimension by box-counting method, and finally classification. The methodology was applied for the detection of three common types of damages: potholes, longitudinal and alligator cracks. Two different supervised learning algorithms, Artificial Neural Networks (ANN) and Support Vector Machine (SVM), were used for classification and results are compared training Convolutional Neural Networks (CNN). The multilayer ANN an overall accuracy of 98.36% and an F-score of 98.33%, while the SVM an accuracy of 97.22% and an F-score of 97.22%. [ABSTRACT FROM AUTHOR]

The existence of road infrastructure such as bridges that do not meet current design criteria, the deterioration of these due to use, environmental factors and extraordinary or unforeseen conditions, and the increase in seismic and gravitational design loads due to regulatory updates, generate the need for search of new design and retrofitting alternatives for this type of structure. Thus, the conditions of these structures need to be assessed and corresponding interventions need to be identified. It is important to implement alternatives that are both economically and functionally efficient. For example, base isolation can reduce direct construction costs by using devices designed and built in the country of origin, but the unfamiliarity and importation costs of these devices are the main obstacles to mass use. In this article, a comparative analysis is performed of a conventional design and an integrated design for base isolation using low-cost unbonded fiber-reinforced elastomeric isolators (U-FREIs) made in Colombia. A methodology is proposed for the analysis of new and existing isolated structures, in which the isolators are placed between the substructure and superstructure. This methodology is used to design and strengthen a typical prestressed concrete girder bridge, and the results are compared against those obtained using a conventional scheme. Finally, an existing bridge is analyzed using on-site measurements to determine the dynamic properties and modify the numerical model used for analysis, design, and retrofitting. The effectiveness of the proposed methodology as a tool for the design of new bridges and the retrofitting of existing structures was verified for all cases. Economic and structural benefits were evidenced by reductions in direct costs of up to 15% and the seismic force of up to 20%, respectively. [ABSTRACT FROM AUTHOR]

For road maintenance and rehabilitation, it is important to develop procedures to evaluate pavement condition. Imaging methods can be used to obtain data to analyze a pavement surface. A methodology for crack detection is presented in this paper that is based on image processing techniques and artificial neural networks. The methodology is implemented in four stages: 1. image acquisition, 2. image processing, 3. feature extraction, and 4. classification using an artificial neural network. The methodology was used to detect deterioration in the form of longitudinal cracks, potholes, and alligator cracking. The classification was performed using a multilayer perceptron (MLP) neural network within a (12 14 3) configuration, resulting in an accuracy of 95.56% and a precision of 94.44%. The proposed methodology could be used to help governmental organizations evaluate a road network. [ABSTRACT FROM AUTHOR]

A large percentage of buildings in Colombia do not have proper earthquake resistance features, as in the case of the city of Cali, where 70% of structures are vulnerable to seismic events. An example of this is the Faculty of Engineering of the del Valle Del Valle University, where the buildings, which were built more than 40 years ago, need to be evaluated and retrofitted according to Regulation NSR-10. However, conventional reinforcement techniques for buildings are highly invasive, disrupt building operations and can be very costly. As an alternative, this article analyzes a retrofitting technique that uses the roof isolation system. In this system, the roof slab is disconnected from the structure and is supported by elastomeric seismic isolators, functioning as a tuned mass damper (TMD), which is an easy configuration due to the type of structure of the Faculty’s buildings. To verify the effectiveness of the proposed system, the buildings were classified into four types according to their geometric characteristics and floor layout, and both the conventional reinforcement and the TMD were designed. A dynamic characterization was obtained through ambient vibration tests, with four seismic accelerometers placed on top of the buildings to identify the predominant frequencies and damping ratios of each vibration mode. The parameters were determined using three identification techniques, and these data were used to fit finite element models of the buildings. The roof isolation system reduces the dynamic response and allows the structural elements to withstand the stress of earthquakes, which shows that the design of the TMD is acceptable. The cost of the roof isolation alternative is between 68 and 86% less than the conventional proposal. This form of seismic retrofitting represents a convenient option for existing buildings of all types of use. [ABSTRACT FROM AUTHOR]

The early detection of cracks, fatigue, corrosion, and structural failure in aging aircraft is one of the major challenges in the aircraft industry. Common inspection techniques are time consuming and hence can have strong economic implications due to aircraft downtime. As a result, during the past decade a number of methodologies have been proposed for detecting structural damage based on variations in the structure's dynamic characteristics. This paper describes the implementation of the natural excitation technique (NEXT) combined with the eigensystem realization algorithm (ERA) to determine the dynamic characteristics of a T-34A Mentor acrobatic category aircraft and a modified DC-3 cargo/transport category aircraft. In-flight acceleration data were processed using NExT-ERA to monitor the predominant natural frequencies and associated mode shapes of the aircraft for varying flight conditions. The results show the effectiveness of this modal identification methodology and the possibility of implementing it in a real-time structural health monitoring system for aircraft. DOI: 10.1061/(ASCE)AS.1943-5525.0000011 CE Database subject headings: Damage; Structural behavior; Monitoring; Aircraft; Safety; Measurement; Modal analysis. Author keywords: Damage; Structural behavior; Monitoring; Aircraft; Safety; Measurement; Modal analysis.